Predicting Stock Market Returns Based on the Content of Annual Report Narrative: A New Anomaly
43 Pages Posted: 31 Jul 2014 Last revised: 20 Aug 2015
Date Written: July 30, 2014
This paper uses the tools of computational linguistics to analyze the qualitative part of annual reports of UK listed companies. More specifically, the frequency of words associated with different language indicators is measured and used to forecast future stock returns. We find that two of these indicators, capturing ‘activity’ and ‘realism’, predict subsequent price increases, even after controlling for a wide range of factors. Elevated values of these two linguistic variables, however, are not symptomatic of exacerbated risk. Consequently, investors are advised to peruse annual report narratives, as they contain valuable information that may not yet have been discounted in the prices.
Keywords: Content Analysis, Annual Reports, Stock Market Returns
JEL Classification: M41; G12; G14
Suggested Citation: Suggested Citation